Estimating link level traffic emissions: enhancing MOVES with open-source data

• URL: http://arxiv.org/abs/2510.03362v1
• Date: Fri, 03 Oct 2025 02:22:56 GMT
• Title: Estimating link level traffic emissions: enhancing MOVES with open-source data
• Authors: Lijiao Wang, Muhammad Usama, Haris N. Koutsopoulos, Zhengbing He,
• Abstract summary: We propose a data-driven framework that integrates MOVES and open-source GPS trajectory data, OpenStreetMap (OSM) road networks, regional traffic datasets and satellite imagery-derived feature vectors.<n>A neural network model is trained to predict the distribution of MOVES-defined operating modes using only features derived from readily available data.<n>Compared to the MOVES baseline, the proposed model reduces RMSE by over 50% for regional scale traffic emissions of key pollutants including CO, NOx, CO2, and PM2.5.
• Score: 14.265166179434061
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Open-source data offers a scalable and transparent foundation for estimating vehicle activity and emissions in urban regions. In this study, we propose a data-driven framework that integrates MOVES and open-source GPS trajectory data, OpenStreetMap (OSM) road networks, regional traffic datasets and satellite imagery-derived feature vectors to estimate the link level operating mode distribution and traffic emissions. A neural network model is trained to predict the distribution of MOVES-defined operating modes using only features derived from readily available data. The proposed methodology was applied using open-source data related to 45 municipalities in the Boston Metropolitan area. The "ground truth" operating mode distribution was established using OSM open-source GPS trajectories. Compared to the MOVES baseline, the proposed model reduces RMSE by over 50% for regional scale traffic emissions of key pollutants including CO, NOx, CO2, and PM2.5. This study demonstrates the feasibility of low-cost, replicable, and data-driven emissions estimation using fully open data sources.

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